TY - JOUR
T1 - Spatial patterning among savanna trees in highresolution, spatially extensive data
AU - Staver, A. Carla
AU - Asner, Gregory P.
AU - Rodriguez-Iturbe, Ignacio
AU - Levin, Simon Asher
AU - Smit, Izak P.J.
N1 - Funding Information:
ACKNOWLEDGMENTS. We thank Juan Bonachela and Sally Archibald for helpful discussion of this work. This collaboration was supported by a grant from the Andrew W. Mellon Foundation, National Science Foundation Division of Mathematical Sciences Grants 1615531 (to A.C.S.) and 1615585 (to S.A.L.), and National Science Foundation Macrosystems Biology Grant 1802453 (to A.C.S.). Airborne LiDAR data collection and processing were made possible by grants from the Andrew W. Mellon Foundation (to G.P.A.). The Carnegie Airborne Observatory has been made possible by grants and donations to G.P.A. from the Avatar Alliance Foundation, Margaret A. Cargill Foundation, David and Lucile Packard Foundation, Gordon and Betty Moore Foundation, Grantham Foundation for the Protection of the Environment, W. M. Keck Foundation, John D. and Catherine T. MacArthur Foundation, Mary Anne Nyburg Baker and G. Leonard Baker Jr., and William R. Hearst III.
Funding Information:
We thank Juan Bonachela and Sally Archibald for helpful discussion of this work. This collaboration was supported by a grant from the Andrew W. Mellon Foundation, National Science Foundation Division of Mathematical Sciences Grants 1615531 (to A.C.S.) and 1615585 (to S.A.L.), and National Science Foundation Macrosystems Biology Grant 1802453 (to A.C.S.). Airborne LiDAR data collection and processing were made possible by grants from the Andrew W. Mellon Foundation (to G.P.A.). The Carnegie Airborne Observatory has been made possible by grants and donations to G.P.A. from the Avatar Alliance Foundation, Margaret A. Cargill Foundation, David and Lucile Packard Foundation, Gordon and Betty Moore Foundation, Grantham Foundation for the Protection of the Environment, W. M. Keck Foundation, John D. and Catherine T. MacArthur Foundation, Mary Anne Nyburg Baker and G. Leonard Baker Jr., andWilliam R. Hearst III.
Publisher Copyright:
© 2019 National Academy of Sciences. All rights reserved.
PY - 2019
Y1 - 2019
N2 - In savannas, predicting how vegetation varies is a longstanding challenge. Spatial patterning in vegetation may structure that variability, mediated by spatial interactions, including competition and facilitation. Here, we use unique high-resolution, spatially extensive data of tree distributions in an African savanna, derived from airborne Light Detection and Ranging (LiDAR), to examine tree-clustering patterns. We show that tree cluster sizes were governed by power laws over two to three orders of magnitude in spatial scale and that the parameters on their distributions were invariant with respect to underlying environment. Concluding that some universal process governs spatial patterns in tree distributions may be premature. However, we can say that, although the tree layer may look unpredictable locally, at scales relevant to prediction in, e.g., global vegetation models, vegetation is instead strongly structured by regular statistical distributions.
AB - In savannas, predicting how vegetation varies is a longstanding challenge. Spatial patterning in vegetation may structure that variability, mediated by spatial interactions, including competition and facilitation. Here, we use unique high-resolution, spatially extensive data of tree distributions in an African savanna, derived from airborne Light Detection and Ranging (LiDAR), to examine tree-clustering patterns. We show that tree cluster sizes were governed by power laws over two to three orders of magnitude in spatial scale and that the parameters on their distributions were invariant with respect to underlying environment. Concluding that some universal process governs spatial patterns in tree distributions may be premature. However, we can say that, although the tree layer may look unpredictable locally, at scales relevant to prediction in, e.g., global vegetation models, vegetation is instead strongly structured by regular statistical distributions.
KW - Heterogeneity
KW - LiDAR
KW - Savanna
KW - Spatial pattern
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U2 - 10.1073/pnas.1819391116
DO - 10.1073/pnas.1819391116
M3 - Article
C2 - 31085650
AN - SCOPUS:85066452997
SN - 0027-8424
VL - 166
SP - 10681
EP - 10685
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 22
ER -